ABSTRACT The proposed project is designed to increase precision and responsiveness in transcranial magnetic stimulation therapies across the neuropsychiatric spectrum and specifically in working memory deficits which are common across a variety of neuropsychiatric conditions. Cutting edge functional imaging studies suggest that using multiple types of imaging datasets yield more reliable estimates of brain network communication. Our methods yield a combined resting and task fMRI functional network mapping individualized for each participant that will allow precise identification of brain stimulation targets associated with optimal working memory performance (Aim 1). To close the loop in designing TMS protocols that respond to an individual person's brain activation state, we will also develop and test a real-time brain decoder to determine when optimal working memory states are online (Aim 2). By iteratively testing excitatory neuromodulation frequencies at this stimulation site and capturing the relative movement of brain states towards or away from optimal working memory states, we will settle on the optimal frequency for augmenting working memory performance in each individual (Aim 3). We will validate this approach by administering either the `best' or `worst' (random assignment to each participant) neuromodulation protocol across several days then testing working memory performance and brain activation in a final MRI scan session. The multi-modal based TMS targeting and individualized frequency optimization techniques will be based on our findings and packaged into a combined software suite in Docker containers made available to the scientific and clinical community at the conclusion of this project (Aim 4).